What question did this study set out to answer?

This research aims to explore the role of the biomarker S100A2 in the pathogenesis of diabetic foot ulcers, particularly through IL-17 signaling.

March 25, 2026Open Access

Neutrophil-Specific Biomarker S100A2 Mediates Diabetic Foot Ulcer Through IL-17 Signaling Pathway and Potential Therapeutics

Key Points

This research aims to explore the role of the biomarker S100A2 in the pathogenesis of diabetic foot ulcers, particularly through IL-17 signaling.
Utilized bulk RNA sequencing and single-cell RNA sequencing datasets from GEO database
Employed analysis packages including limma, WGCNA, CIBERSORT, and Seurat
Validated immune hub gene expression using quantitative real-time PCR and RNA-seq data
Conducted computational drug prediction using the Connectivity Map database
Identified seven immune hub genes through bulk RNA-seq analysis
Recognized six specific cell populations via scRNA-seq, with S100A2 mainly expressed in neutrophils
Establish a strong link between S100A2 and the IL-17 signaling pathway
Identified secukinumab, ruxolitinib, and leflunomide as potential therapeutic drugs for diabetic foot ulcers

Abstract

Background: Diabetic foot ulcers (DFU) often lead to infection and amputation, thereby imposing a heavy socioeconomic burden. The limited efficacy of current therapies underscores the urgent need to explore the pathogenesis of DFU. Alterations in the immune response have been reported to influence the pathophysiology of DFU by single-cell RNA sequencing (scRNA-seq) analysis. Therefore, a thorough understanding of the immune microenvironment characteristics of DFU and the intervention of specific immune cell populations could enable the formulation of optimal therapeutic strategies. Methods: Bulk RNA sequencing (bulk RNA-seq) datasets and scRNA-seq datasets were acquired from the Gene Expression Omnibus (GEO) database. The packages “limma”, “weighted gene coexpression network analysis (WGCNA)”, and “CIBERSORT” were used for bulk RNA-seq analysis to identify the key immune genes. For scRNA-seq, the packages “Seurat” were used for cell clusters identification and annotation. The differential expression of immune hub genes between DFU and diabetic foot skin (DFS) was validated using quantitative real-time polymerase chain reaction (qRT-PCR) and our RNA-seq dataset. A Connectivity Map (CMAP) database was used for computational drug prediction. Results: Using bulk-RNA-seq, seven genes were identified as immune hub genes. Afterwards, six cell populations were recognized by scRNA-seq, with S100A2 predominantly expressed in neutrophils. Moreover, we revealed a robust correlation between the interleukin-17 (IL-17) signaling pathway and S100A2. Secukinumab, ruxolitinib, and leflunomide are potential therapeutic drugs for DFU. Among them, ruxolitinib and leflunomide are clinically available agents, while secukinumab (an IL-17A inhibitor) shows translational potential for repurposing. Conclusion: S100A2 appears to be a promising therapeutic target for the modulation of DFU pathogenesis. Furthermore, neutrophil-mediated inflammatory responses and immune regulation appear to be crucial factors in DFU progression. Notably, this is the first study to identify S100A2 as a neutrophil-specific biomarker linked to IL-17 signaling in DFU, filling the gap of specific gene-immune cell interaction in DFU pathogenesis. Keywords: diabetic foot ulcer, single-cell RNA sequencing, immune infiltration, IL-17 signaling pathway, drug prediction

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